@inproceedings{cd2cdc9e0b404e5fa621ea900860ceb9,
title = "Automatic detection of surgical phases in laparoscopic videos",
abstract = "The assement and evaluation of surgical skills require a considerable amount of time and effort. Currently, the assessment is accomplished by either observing a recorded video from the surgery in the case of laparoscopic procedures, or watching it in real-time in an operating room in the case of open surgical procedures. Given the limited time available to experts, knowing the surgical workflow can expedite the process of assessment by helping the surgeons to focus on the most important parts of each surgical phase. In this paper, we developed a method called Surgical Phase Detection using a Deep Learning System (SPD-DLS) to identify the surgical phases from recorded videos of a laparoscopic procedure. We used a deep Convolutional Neural Network (CNN) followed by a Long Short-Term Memory (LSTM) model to consider both spatial and temporal information to identify the surgical phases in the video frames. In order to evaluate the resulting model, we used the publicly available cholec80 dataset, which contains 80 videos of laparoscopic cholecystectomy procedure. Our experimental results show significant improvement in both real-time and off-line modes in the automatic identification of surgical phases over existing methods that use the same dataset.",
keywords = "Convolutional neural networks, Deep Learning, LSTM, Surgical workflow",
author = "Babak Namazi and Ganesh Sankaranarayanan and Venkat Devarajan",
note = "Publisher Copyright: CSREA Press {\textcopyright}.; 2018 International Conference on Artificial Intelligence, ICAI 2018 at 2018 World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2018 ; Conference date: 30-07-2018 Through 02-08-2018",
year = "2018",
language = "English (US)",
series = "2018 World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2018 - Proceedings of the 2018 International Conference on Artificial Intelligence, ICAI 2018",
publisher = "CSREA Press",
pages = "124--130",
editor = "Arabnia, {Hamid R.} and {de la Fuente}, David and Kozerenko, {Elena B.} and Olivas, {Jose A.} and Tinetti, {Fernando G.}",
booktitle = "2018 World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2018 - Proceedings of the 2018 International Conference on Artificial Intelligence, ICAI 2018",
}